An Intemational Journal computers & .=.=.c= C~o,,,=~T. mathematics · 2016. 12. 7. · The Book Reports section is a regular feature of Computers 8_t Mathematics with Applications.

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An Intemational Journal Available online at www.sciencedirect.com computers &

.= .= .c= C~o,, ,=~T. mathemat ics with applications

Computers and Mathematics with Applications 51 (2006) 1149-1162 www.elsevier.com/locat e/camwa

B O O K R E P O R T S The Book Repor t s section is a regular feature of Computers 8_t Mathematics with Applications.

It is an unconventional section. The Edi tors decided to break with the longs tanding cus tom of

publishing ei ther lengthy and discursive reviews of a few books, or j u s t a brief l is t ing of t i t les.

Instead, we decided to publish every impor t an t mate r ia l de ta i l concerning those books submi t t ed

to us by publishers, which we judge to be of potent iM interest to our readers. Hence, breaking

with custom, we also publish a complete table of contents for each such book, bu t no review of it as such. We welcome our readers ' comments concerning this enterprise. Publ ishers should

submit books in tended for review to the Edi tor- in-Chief ,

Professor Ervin Y. Rodin

Campus Box 1040

Washington Univers i ty in St. Louis

One Brookings Drive

St Louis, MO 63130, U.S.A.

0898-1221/06/$ - see front matter (~ 2006 Elsevier Ltd. All rights reserved. Typeset by ~4~fS-TEX doi: 10.1016/j .camwa. 2006.03.015

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Linear Programminq and Network Flows Mokhtar S. Bazaraa, John J. Jarvis, Hanif D. Sheral, Wiley Publishers, Hoboken, N J, 2005, 726 pages. $94.95. Contents ONE: Introduction 1.1. The Linear Programming Problem. 1.2. Linear Programming Modeling and Examples. 1.3. Geometric Solution. 1.4. The Requirement Space. 1.5. Notation. Exercises. Notes and References. TWO: Linear Algebra, Convex Analysis, and Polyhedral Sets 2.1. Vectors. 2.2. Matrices. 2.3. Simultaneous Linear Equations. 2.4. Convex Set and Convex Functions. 2.5. Polyhedral Sets and Plyhedral Cones. 2.6. Extreme Points,Faces,Directions,and Extreme Directions of Polyhedral Sets: Geometric Insights. 2.7. Representation of Polyhedral Sets. Exercises. Notes and References. THREE: The Simplex Method 3.1. Extreme Points and Optimality. 3.2. Basic Feasible Solutions. 3.3. Key to the Simplex Method. 3.4. Geometric Motivation of the Simplex Method. 3.5. Algebra of the Simplex Method, 3.6. Termination: Optimalty and Unboundedness. 3.7. The Simplex Method. 3.8. The Simplex Method in Tableau Format. 3.9. Block Pivoting. Exercises. Notes and References. FOUR: Starting Solution and Covergence 4.1. The Initial Basic Feasible Solution. 4.2. The Two-Phase Method. 4.3. The Big-M Method. 4.4. How Big Should Big-M Be. 4.5. The Single Artificial Variable Technique. 4.6. Degeneracy,Cycling, and Stalling. 4.7. Validation of the Two Cycling Prevention Rules. Exercises. Notes and References. FIVE: Special Simplex Implementations and Optimality Conditions 5.1. The Revised Simplex Method. 5.2. The Simplex Method for Bounded Variables. 5.3. Farkas' Lemma via the Simplex Method. 5.4. The Karush-Kuhn- Tucker Optimality Conditions. Exercises. Notes and References. SIX: Duality and Sensitivity Analysis 6.1. Formulation of the Dual Problem. 6.2. PrimM-Dual Relationships. 6.3. Economic Interpretation of the Dual. 6.4. The Dual Simplex Methods. 6.5. The Prima-Dual Method. 6.6. Finding an Intitial Dual Feasible Solution:The Artificial Constraint Technique. 6.7. Sensitivity Analysis. 6.8. Parametric Analysis. Exercises. Notes and References. SEVEN: The Decomposition Principle 7.1. The Decomposition Principle. 7.2. Numerical Example. 7.3. Getting Started. 7.4. The Case of Unbounded Region X. 7.5. Block Diagonal or Angular Structure. 7.6. Duality and Relationships with other Decomposition Procedures. Exercises. Notes and References. EIGHT: Complexity of The Simplex Algorithm And Polynomial Algorithms 8.1. Polynomial Complexity Issues. 8.2. Computational Complexity of the Simplex Algorithm. 8.3. Khachian's Ellipsoid Algorithm. 8.4. Karmarkar's Projective Algorithm. 8.5. Analysis of Karmarkar's Algorithm: Convergence Complexity, Sliding Objective Method, and Basic Optimal Solutions. 8.6. Affine Scaling, Primal-Dual Path-Following, and Predictor-Corrector Variants of Interior Point Methods. Exercises. Notes and References. NINE: Minimal-Cost Network Flows 9.1. The Minimal-Cost Network Flow Problem. 9.2. Some Basic Defintions and Terminology from Graph Theory. 9.3. Properties of the A Matrix. 9.4. Representation of a Nonbasic Vector in Terms of the Basic Vectors. 9.5. The Simplex Method for Network Flow Problems. 9.6. An Example of the Network Simplex Method. 9.7. Finding and Initial Basis Feasible Solution. 9.8. Network Flows with Lower and Upper Bounds. 9.9. Simplex Tableau Associated with a Network Flow Problem. 9.10. List Structure for Implementing the Network Simplex Alogrithm. 9.11. Degeneracy, Cycling,and Stalling. 9.12. Generalized Network Problems. Exercises. Notes and References. TEN: The Transportation and Assignment Problems 10.1. Defintion of the Transportation Problem. 10.2. Prop- erties of the A Matrix. 10.3. Representation of a Nonbasic Vector in Terms of Basic Vectors. 10.4. The Simplex Method for Transportation Problems. 10.5. Illustrative Examples and a note on Degeneracy. 10.6. The Simplex Tableau Associated with a Transportation Tableau. 10.7. The Assignment problem:(Kuhn's)Hungarian Algo- rithm. I0.8. Alternation Basis Algorithm for Assignment Problems. 10.9. A Polynomial Successive Shortest Path Approach for Assignment Problems. 10.10. The Transshipment Problem. Exercises. Notes and References. ELEVEN: The Out-of-Kilter Algorithm 11.1. The Out-of-Kilter Formulation of a Minimal Cost Network Flow Problem. 11.2. Strategy of the Out-of-Kilter Algorithm. 11.3. Summary of the Out-of-Kilter Algorithm. 11.4. An Example of the Out-of-Kilter Algorithm. 11.5. A Labeling Procedure for the Out-of-Kilter Algorithm. 11.6. Insight into Changes in Primal and Dual Function Values. 11.7. Relaxation Algorithms. Exercises. Notes and References. TWELVE: Maximal Flow,Shortest Path,Multicommodity Flow,and Network Synthesis Problems 12.1. The Max- imal Flow Problem. 12.2. The Shortest Path Problem. 12.3. Polynomial Shortest Path Algorithms for Networks Having Arbitrary Costs. 12.4. Multicommodity Flows. 12.5. Characterization of a Basis for Multicommodity Minimal-Cost Flow Problem. 12.6. Synthesis of Multterminal Flows Networks. Exercises. Notes and References. Bbibliography Index

Health and Economic Growth, Findinqs and Policy Implication Guillem Lopez-Casanovas, Berta Rivera, Luis Currais, The MIT Press, Cambridge, MA, 385 pages, $45.00. Contents. Preface by Guillem Lopez-Casanovas. Acknowledgments. Introduction: The Role Health Plays in Economic Growth. I. Health,Human Capital, and Economic Growth. 1. Health,Human Capital, and Economic Growth: A Schum- peterian Perspective. 2. Health as a Principal Determinant of Economic Growth. 3. Health's Contribution to Economic Growth in an Environment of Partially Endogenous Technical Progress.

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II. Macroeconomics, Development, and Health. 4. On the Health-Poverty Trap. 5. Human Development Traps and Economic Growth. 6. Health, Education, and Economic Development. 7. Nutrition, Malnutrition, and Economic Growth. III. Human Capital, Health, and Demography. 8. On Epidemiologic Transitions A Historical View. 9. Economic Growth, Health, and Longevity in the Very Long Term: Facts and Mechanisms. IV. Productivity, Labor Markets, and Health. 10. Productive Benefits of Health: Evidence from Low-Income Countries. 11. Individual Returns to Health in Brazil: A Quantile Regression Analysis. V. Quantity of Life and the Welfare Costs of AIDS. 12. The Economic Cost of AIDS in Sub-Saharan Africa: A Reassessment. 13. Profits and People: On the Incentives of Business to Get Involved in the Fight against AIDS. Conclusion. Contributors. Index.

MuPAD Tutorial Enqlish Edition. Christopher Creutzig and Walter Oevel. Springer. Heidelberg, Germany. 2004. 412 pages. $59.95. Contents: Preface. Chapter 1. Introduction. 1 .1 . Numerical Computations. 1 .2 . Computer Algebra. 1 .3 . Characteristics of Computer Algebra Systems. 1.4. Existing Systems. 1.5. MuPAD. Chapter 2. First Steps in MuPAD 2.1. Explanations and Help. 2.2. Computing with Numbers 2.2.1. Exact Computations. 2.2.2. Numerical Approximations. 2.2.3. Complex Numbers. 2.3. Symbolic Computation. 2.3.1. Introductionary Examples. 2.3.2. Curve Sketching. 2.3.3. Elementary Number Theory. Chapter 3. The MuPAD Libraries. 3.1. Information About a Particular Library. 3.2. Exporting Libraries. 3.3. The Standard Library. Chapter 4. MuPAD Objects. 4.1. Operands: The Functions op and nops. 4.2. Numbers. 4.3. Identifiers. 4.4. Symbolic Expressions. 4.4.1. Operators. 4.4.2. Expression Trees. 4.4.3. Operands. 4.5. Sequences. 4.6. Lists. 4.7. Sets. 4.8. Tables. 4.9. Arrays. 4.10. Boolean Expressions. 4.11. Strings. 4.12. Functions. 4.13. Series Expansions. 4.14. Algebraic Structures: Fields, Rings, etc. 4.15. Vectors and Matrices. 4.15.1. Definition of Matrices and Vectors. 4.15.2. Computing with Matrices. 4.15.3. Special Methods for Matrices. 4.15.4. The Libraries linalg and numeric. 4.15.5. Sparce Matrices. 4.15.6. An Application. 4.16. Polynomials. 4.16.1. Definition of Polynomials. 4.16.2. Computing with Polynomials. 4.17. Interval Arithmetic. 4.18. Null Objects: null(), NIL, GAIL, undefined. Chapter 5. Evaluation and Simplification. 5.1. Identifiers and Their Values. 5.2. Complete, Incomplete, and Enforced Evaluation. 5.3. Automatic Simplification. Chapter 6. Substitution: subs, subsex, and subsop. Chapter 7. Differentiation and Integration 7.1. Differentiation 7.2. Integration Chapter 8. Solving Equations: solve 8.1. Polynomial Equations. 8.2. General Equations and Inequalities. 8.3. Differential Equations. 8.4. Recurrence Equations. Chapter 9. Manipulating Expressions. 9.1. Transforming Expressions. 9.2. Simplifying Expressions. 9.3. Assumptions About Symbolic Identifiers. Chapter 10. Chance and Probability. Chapter 11. Graphics. 11.1. Introduction. 11.2. Easy Plotting: Graphs of Functions. 11.2.1. 2D Function Graphs: plotfunc2d. 11.2.2. 3D Function Graphs: plotfunc3d. 11.3. Advanced Plotting: Principles and First Examples. 11.3.1. General Principles. 11.3.2. Some Examples. 11.4. The Full Picture: Graphical Trees. 11.5. Viewer, Browser, and Inspector: Interactive Manipulation. 11.6. Primitives. 11.7. Attributes. 11.7.1 Default Values. 11.7.2 Inheritance of Attributes. 11.7.3. Primitives Requesting Scene Attributes: "Hints". 11.7.4. The Help Pages of Attributes. 11.8. Colors. 11.8.1. RGB Colors. 11.8.2. HSV Colors. 11.9. Animations. 11.9.1. Generating Simple Animations. 11.9.2. Playing Animations. 11.9.3. The Number of Frames and the Time Range. 11.9.4. What Can Be Animated? 11.9.5. Advanced Animations: The Synchronization Model. 11.9.6. Frame by Frame Animations. 11.9.7. Examples. 11.10. Croups of Primitives. 11.11. Transformations. 11.12. Legends. 11.13. Fonts. 11.14. Saving and Exporting Pictures. 11.14.1. Interactive Saving and Exporting. 11.14.2. Batch Mode. 11.15. Importing Pictures. 11.16. Cameras in 3D. 11.17. Strange Effects in 3D? Accelerated OpenGL? Chapter 12. The History Mechanism. Chapter 13. Input and Output. 13.1. Output of Expressions. 13.1.1. Printing Expressions on the Screen. 13.1.2. Modifying the Output Format. 13.2. Reading and Writing Files. 13.2.1. The Functions write and read. 13.2.2. Saving a MuPAD Session. 13.2.3. Reading Data from a Text File. Chapter 14. Utilities. 14.1. User-Defined Preference. 14.2. Information on MuPAD Algorithms. 14.3. Restarting a MuPAD Session. 14.4. Executing Commands of the Operating System. Chapter 15. Type Specifiers. 15.1. The Functions type and testtype. 15.2. Comfortable Type Checking: The Type Library. Chapter 16. Loops. Chapter 17. Branching: if-then-else and case. Chapter 18. MuPAD Procedures. 18.1. Defining Procedures. 18.2. The Return Value of a Procedure. 18.3. Returning Symbolic Function Calls. 18.4. Local and Global Variables. 18.5. Subprocedures. 18.6. Scope of Variables. 18.7. Type Declaration. 18.8. Procedures with a Variable Number of Arguments. 18.9. Options: The

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Remember Table. 18.10. Inpu t Parameters . 18.11. Evaluat ion Wi th in Procedures . 18.12. Funct ion Environments . 18.13. A P rog rammi ng Example: Differentiation. 18.14. P rog ramming Exercises. Appendix A. Solutions to Exercises. Appendix B. Documenta t ion and References. Appendix C. Graphics Gallery. Appendix D. C o m m e n t s on the Graphics Gallery. Index.

Comprehensive Mathematics [or Computer Scientists 2. Guerino Mazzola, G 'e ra rd Milmeister and Jody Weiss- mann. Springer. Heidelberg, Germany. 2005. 355 pages. $39.95. Contents : Par t III Topology and Calculus. Chapte r 27. Limits and Topology. 27.1. Introduction. 27.2, Topologies on Real Vector Spaces. 27.3. Continuity. 27.4. Series. 27.5. Euler 's Formula for Polyhedra and Kuratowski ' s Theorem. Chapte r 28. Differentiability. 28.1. Introduction. 28.2. Differentiation. 28.3. Taylor 's Formula. Chapte r 29. Inverse and Implicit Functions. 29.1. Introduct ion. 29.2. The Inverse Funct ion Theorem. 29.3. The Implicit Funct ion Theorem. Chapte r 30. Integration. 30.1. Introduction. 30.2. Par t i t ions and the Integral. 30.3. Measure and Integrability. Chapte r 31. The Fundamenta l Theorem of Calculus and Fubini 's Theorem. 31.1. Introduct ion. 31.2. The Fundamen ta l Theorem of Calculus. 31.3. Fubini 's Theorem on I terated Integrat ion. Chapte r 32. Vector Fields. 32.1. Introduction. 32.2. Vector Fields. Chapte r 33. Fixpoints . 33.1. Introduction. 33.2. Contract ions. Chapte r 34. Main Theorem of ODE ' s 34.1. Introduct ion. 34.2. Conservat ive and T ime-Dependen t Ordinary Differential Equat ins: T he Local Setup. 34.3. The Fundamenta l Theorem: Local Version. 34.4. The Special Case of a Linear ODE. 34.5. T he Fundamenta l Theorem: Global Version. Chapter 35. Th i rd Advanced Topic. 35.1. Introduction. 35.2. Numerics of ODE. 35.3. T h e Euler Method. 35.4. R u n g e - K u t t a Methods . Par t IV Selected Higher Subjects. Chapte r 36. Categories. 36.1. Introduction. 36.2. W h a t Categories Are. 36.3. Examples . 36.4. Functors and Natura l Transformat ions . 36.5. Limits and Colimits. 36.6. Adjunct ion. Chapte r 37. Splines. 37.1. Introduction. 37.2. Prel iminaries on Simplexes. 37.3. W h a t are Splines? 37.4. Lagrange Interpolation. 37.5. B'ezier Curves. 37.6. Tensor Product Splines. 37.7. B-Splines. Chapte r 38. Fourier Theory. 38.1. Introduction. 38.2. Spaces of Periodic Functions. 38.6. Orthogonali ty. 38.4. Fourier 's Theorem. 38.5. Res t a t emen t in Terms of the Sine and Cosine Functions. 38.6. Fini te Fourier Series and Fast Fourier Transform. 38.7. Fast Fourier Transform (FFT). 38.8. The Fourier Transform. Chapte r 39. Wavelets. 39.1. Introduction. 39.2. The Hilbert Space L2II{. 39.3. Frames and Or thonormal Wavelet Bases. 39.4. The Fast Haar Wavelet Transform. Chapte r 40. Fractals. 40.1. Introduction. 40.2. Hausdorff-IvIetric Spaces. 40.3. Contrac t ions on Hausdorff-Metric Spaces. 40.4. Fractal Dimension. Chapte r 41. Neural Networks. 41.1. Introduction. 41.2. Formal Neurons. 41.3. Neural Networks. 41.4. Mult i-Layered Perceptrons. 41.5. The Back-Propogat ion Algori thm. Chapter 42. Probabil i ty Theory. 42.1. Introduction. 42.2. Event Spaces and R a n d o m Variables. 42.3. Probabili ty Spaces. 42.4. Dis t r ibut ion Functions. 42.5. Expecta t ion and Variance. 42.6. Independence and the Central Limit Theorem. 42.7. A Remark on Inferential Statistics. Chapte r 43. L a m b d a Calculus. 43.1. Introduction. 43.2. The L a m b d a Language. 43.3. Subst i tut ion. 43.4. Alpha-Equivalence. 43,5. Beta-Reduct ion. 43.6. T he A-Calculus as a P r o g r a m m i n g Language. 43.7. Recursive Functions. 43.8. Representa t ion of Part ial Recursive Functions. Appendix A. Fur ther Reading. Appendix B. Bibliography. Index.

Makinq Modern Science. A Historical Survey.. Peter J. Bowler and Iwan Rhys Morus. Universi ty of Chicago Press. Chicago, IL. 2005. 529 pages. $25.00. Contents: Preface. Chapte r 1. Introduct ion: Science, Society, and History. Par t I. Chapter 2. The Scientific Revolution. Chapter 3. The Chemical Revolution. Chapte r 4. The Conservat ion of Energy. Chapte r 5. The Age of the Earth. Chap te r 6. The Darwinian Revolution. Chapte r 7. The New Biology. Chapte r 8. Genetics. Chapter 9. Ecology and Environmental ism. Chapter 10. Cont inenta l Drift. Chapter 11. Twent ie th~Century Physics. Chapter 12. Revolutionizing Cosmology. Chapter 13. The Emergence of the H u m a n Sciences. Par t II. Themes in the History of Science.

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Chapter 14. The Organization of Science. Chapter 15. Science and Religion. Chapter 16. Popular Science. Chapter 17. Science and Technology. Chapter 18. Biology and Ideology. Chapter 19. Science and Medicine. Chapter 20. Science and War. Chapter 21. Science and Gender. Chapter 22. Epilogue. Index.

Readinqs in Database S~tstems. Fourth Edition. Edited by Joseph M. Hellerstein and Michael Stonebraker. The MIT Press. Cambridge, MA. 2005. 865 pages. $55.00. Contents: Preface. Chapter 1. Data Models and DBMS Architecture. What Goes Around Comes Around. Anatomy of a Database System. Chapter 2. Query Process. Access Path Selection in a Relational Database Management System. Join Processing in Database System with Large Main Memories. Parallel DAtabase Systems: The Future of High Performance Database Systems. Encapsulation of Parallelism in the Volcano Query Processing System. AlphaSort: A RISC Machine Sort. R* Optimizer Validation and Performance Evaluation for Distributed Queries. Mariposa: A Wide-Area Distributed Database System. Chapter 3. Data Storage and Access Methods. Introduction. The R*-tree: An Efficient and Robust Access Method for Points and Rectangles. Operating System Support for Database Management. The Five-Minute Rule Ten Years Later, and Other Computer Storage Rules of Thumb. A Case of Redundant Arrays of Inexpensive Disks (RAID). Chapter 4. Transaction Management. Introduction. Granularity of Locks and Degrees of Consistency in a Shared Data Base. On Optimistic Methods for Concurrency Control. Concurrency Control Performance Modeling: Alternatives and Implications. Efficient Locking for Concurrent Operations on B-Trees. ARIES: A Transac- tion Recovery Method Supporting Fine-Granularity Locking and Partial Rollbacks Using Write-Ahead Logging. Transaction Managementin the R* Distributed Database Management System. The Dangers of Replication and a Solution. Chapter 5. Extensibility. Introduction. Inclusion of New Types in Relational Data Base Systems. General- ized Search Trees for Database Systems. Grammar-like Functional Rules for Representing Query Optimization Alternatives. Chapter 6. Database Evolution. Introduction. AutoAdmin "What-if' Index Analysis Utility. Applying Model Management to Classical Mega Data Problems. Algorithms for Creating Indexes for Very Large Tables Without Quiescing Updates. Chapter 7. Data Warehousing. Introduction. An Overhead of Data Warehousing and OLAP Technology. Im- proved Query Performance with Variant Indexes. DataCube: A Relational Aggregation for Simultaneous Mul- tidimensional Aggregates. An Array-Based Algorithm for Simultaneous Multidimensional Aggregates. Deriving Production Rules for Incremental View Maintenance. Informix under CONTROL: Online Query Processing. DynaMat: A Dynamic View Management System for Data Warehouses. Chapter 8. Data Mining. Introduction. BIRCH: An Efficient Data Clustering Method for Very Large Databases. SPRINT: A Scalable Parallel Classifier for Data Mining. Fast Algorithms for Mining Association Rules. Efficient Evaluation of Queries with Mining Predicates. Chapter 9. Web Services and Data Bases. Introduction. Combining Systems and Databases: A Search Engine Ret- rospective. The Anatomy of a Large-Scale Hypertextual Web Search Engine. The BINGO! System for Information Portal Generation and Expert Web Search. Data Management in Application Servers. Querying Semi-Structured Data. DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases. NiagaraCQ: A Scalable Continuous Query System for the Internet Databases. Chapter 10. Stream-Based Data Management. Introduction. Scalable Trigger Processing. The Design and Implementation of a Sequence Database System. Eddies: Continuously Adaptive Query Processing. Retrospective on Aurora. Sources.

Applied Numerical Methods Usinq MATLAB. Won Y. Yang, Wenwu Cao, Tae-Sang Chung and John Morris. Wiley. Hoboken, NJ. 2005. 509 pages. $99.95. Contents: Chapter 1. MATLAB Usage and Computational Errors. 1.1. Basic Operations of MATLAB. 1.1.1. Input/Output of Data from MATLAB Command Window. 1.1.2. Input/Output of Data Through Files. 1.1.3. Input/Output of Data Using Keyboard. 1.1.4. 2-D Graphic Input/Output. 1.1.5. 3-D Graphic Output. 1.1.6. Mathematical Functions. 1.1.7. Operations on Vectors and Matrices. 1.1.8. Random Number Generators. 1.1.9. Flow Control. 1.2. Computer Errors Versus Human Mistakes. 1.2.1. IEEE 64-Bit Floating-Point Number Representation. 1.2.2. Various Kinds of Computing Errors. 1.2.3. Absolute/Relative Computing Errors. 1.2.4. Error Propagation. 1.2.5. Tips for Avoiding Large Errors. 1.3. Toward Good Program. 1.3.1. Nested Computing for Computational

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Efficiency. 1.3.2. Vector Operation Versus Loop Iteration. 1.3.3. Iterative Routine Versus Nested Routine. 1.3.4. To Avoid Runtime Error. 1.3.5. Parameter Sharing via Global Variables. 1.3.6. Parameter Passing Through Varargin. 1.3.7. Adaptive Input Argument List. Problems. Chapter 2. System of Linear Equations. 2.1. Solution for a System of Linear Equations. 2.1.1. The Nonsingular Case (M = N). 2.1.2. The Underdetermined Case (M < N): Minimum-Norm Solution. 2.1.3. The Overdeter- mined Case (M > N): Least-Squares Error Solution. 2.1.4. RLSE (Recursive Least-Squares Estimation). 2.2. Solving a System of Linear Equations. 2.2.1. Gauss Elimination. 2.2.2. Partial Pivoting. 2.2.3. Gauss-Jordan Elimination. 2.3. Inverse Matrix. 2.4. Decomposition (Factorization). 2.4.1. LU Decomposition (Factorization): Triangularization. 2.4.2. Other Decomposition (Factorization): Cholesky, QR, and SVD. 2.5. Iterative Methods to Solve Equations. 2.5.1. Jacobi Iteration. 2.5.2. Gauss-Seidel Iteration. 2.5.3. The Convergence of Jacobi and Gaus-Seidel Iterations. Problems. Chapter 3. Interpolation and Curve Fitting. 3.1. Interpolation by Lagrange Polynomial. 3.2. Interpolation by Newton Polynomial. 3.3. Approximation by Chebyshev Polynomial. 3.4. Pade Approximation by Rational Function. 3.5. Interpolation by Cubic Spline. 3.6. Hermite Interpolating Polynomial. 3.7. Two-DimensionM Interpolation. 3.8. Curve Fitting. 3.8.1. Straight Line Fit: A Polynomial Function of First Degree. 3.8.2. Polynomial Curve Fit: A Polynomial Function of Higher Degree. 3.8.3. Exponential Curve Fit and Other Functions. 3.9. Fourier Transform 3.9.1. FFT Versis DFT. 3.9.2. Physical Meaning of DFT. 3.9.3. Interpolation by Using DFS. Problems. Chapter 4. Nonlinear Equations. 4.1. Iterative Method Toward Fixed Point. 4.2. Bisection Method. 4.3. False Position or Regula Falsi Method. 4.4. Newton(-Raphson) Method. 4.5. Secant Method. 4.6. Newton Method for a System of Nonlinear Equations. 4.7. Symbolic Solution for Equations. 4.8. A ReM-World Problem. Problems. Chapter 5. Numerical Differentiation/Integration. 5.1. Difference Approximation for First Derivative. 5.2. Approximation Error of First Derivative. 5.3. Difference Approximation for Second and Higher Derivative. 5.4. Interpolating Polynomial and Numerical Differential. 5.5. Numerical Integration and Quadrature. 5.6. TRapezoidal Method and Simpson Method. 5.7. Recursive Rule and Romberg Integration. 5.8. Adaptive Quadrature. 5.9. Gauss Quadrature. 5.9.1. Gauss-Legendre Integration. 5.9.2. Gauss-Hermite Integration. 5.9.3. Gauss-Laguerre Integration. 5.9.4. Gauss-Chebyshev Integration. 5.10. Double Integral. Problems. Chaptcr 6. Ordinary Differential Equations. 6.1. Euler's Method. 6.2. Heun's Method: Trapezoidal Method. 6.3. Runge-Kutta Method. 6.4. Predictor-Corrector Method. 6.4.1. Adams-Bashforth-Moulton Method. 6.4.2. Hamming Method. 6.4.3. Comparison of Methods. 6.5. Vector Differential Equations. 6.5.1. State Equation. 6.5.2. Discretization of LTI State Equation. 6.5.3. High-Order Differential Equation to State Equation. 6.5.4. Stiff Equation. 6.6 Boundary Value Problem (BVP). 6.6.1. Shooting Method. 6.6.2. Finite Difference Method. Chapter 7. Optimization. 7.1. Unconstrained Optimization [-2, Chapter 7]. 7.1.1. Golden Search Method. 7.1.2. Quadratic Approximation Method. 7.1.3. Nelder-Mead Method. 7.1.4. Steepest Descent Method. 7.1.5. Newton Method. 7.1.6. Conjugate Gradient Method. 7.1.7. Simulated Annealing Method. 7.1.8. Genetic Algorithm [w-7]. 7.2. Constrained Optimization [L-2, Chapter 10]. 7.2.1. Lagrange Multiplier Method. 7.2.2. Penalty Function Method. 7.3. MATLAB Built-In Routines for Optimization. 7.3.1. Unconstrained Optimization. 7.3.2. Constrained Optimization. 7.3.3. Linear Programming (LP). Problems. Chapter 8. Matrices and Eigenvalues. 8.1. Eigenvalues and Eigenvectors. 8.2. Similarity Transformation and Diagonalization. 8.3. Power Method. 8.3.1. Scaled Power Method. 8.3.2. Inverse Power Method. 8.3.3. Shifted Inverse Power Method. 8.4. Jacobi Method. 8.5. Physical Meaning of Eigenvalues/Eigenvectors. 8.6. Eigenvalue Equations. Problems. Chapter 9. Partial Differential Equations. 9.1. Elliptic PDE. 9.2. Parabolic PDE. 9.2.1. The Explicit Forward Euler Method. 9.2.2. The Implicit Backward Euler Method. 9.2.3. The Crank-Nicholson Method. 9.2.4. Two- Dimensional Parabolic PDE. 9.3. Hyperbolic PDE. 9.3.1. The Explicit Central Difference Method. 9.3.2. Two- Dimensional Hyperbolic PDE. 9.4. Finite Element Method (FEM) for Solving PDE. 9.5. GUI or MATLAB for Solving PDEs: PDETOOL. 9.5.1. Basic PDEs Solvable by PDETOOL. 9.5.2. The Usage of PDETOOL. 9.5.3. Examples of Using PDETOOL to Solve PDEs. Problems. Appendices. Appendix A. Mean Value Theorem. Appendix B. Matrix Operations/Properties. Appendix C. Differentiation with Respect to a Vector. Appendix D. Laplace Transform. Appendix E. Fourier Transform. Appendix F. Useful Formulas. Appendix G. Symbolic Computation. Appendix H. Sparse Matrices. Appendix I. MATLAB. References. Subject Index. Index for MATLAB Routines. Index for Tables.

Quantum Information Processinq. Second, revised and enlarged Edition. Edited by Thomas Beth and Gerd Leuchs. Wiley-VCH. Hoboken, NJ. 2005. 449 pages. $205.00.

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Contents: List of Contributors. Chapter i. Algorithms for Quantum Systems--Quantum Algorithms. i.I. Introduction. 1.2. Fast Quantum Signal Transforms. 1.3. Quantum Error-Correcting Codes. 1.4. Efficient Decomposition of Quantum Operations into Given One-Parameter Groups. 1.5. Simulation of Hamiltonians. References. Chapter 2. Quantum Information Processing and Error Correction with Jump Codes. 2.1. Introduction. 2.2. Invertible Quantum Operations and Error Correction. 2.3. Quantum Error COrrection by Jump Codes. 2.3.1. Spontaneous Decay and Quantum Trajectories. 2.3.2. Jump Codes. 2.4. Universal Quantum Gates in Code Spaces. 2.4.1. Universal Sets of Quantum Gates for Qudit-Systems. 2.4.2. Universal One-Qutrit Cates. 2.4.3. A Universal Entanglement Gate. 2.5. Summary and Outlook. References. Chapter 3. Introduction. Computational Model for the One-Way Quantum Computer: Concepts and Summary. 3.1. Introduction. 3.2. The QCc as a Universal Simulator of Quantum Logic Networks. 3.3. Non-Network Character of the QCcaIC. 3.4. Computational Model. 3.5. Conculsion. References. Chapter 4. Quantum Correlations as Basic Resource for Quantum Key Distribution. 4.1. Introduction. 4.2. Background of Classical Information Theoretic Security. 4.3. Link Between Classical and Quantum. 4.4. Searching for Effective Entanglement. 4.5. Verification Sets. 4.5.1. 6-State Protocol. 4.5.2. 4-State Protocol. 4.5~3. 2-State Protocol. 4.6. Examples for Evaluation. 4.7. Realistic Experiments. 4.8. Conclusions. References. Chapter 5. Increasing the Size of NMR Quantum Computers. 5.1. Introduction. 5.2. Suitable Molecules. 5.3. Scaling Problem for Experiments Based on Pseudo-Pure States. 5.4. Approaching Pure States. 5.5. Scalable NMR Quantum Computing Based on the Thermal Density Operator. 5.6. Time-Optimal Implementation of Quantum Gates. 5.7. Conclusion. References. Chapter 6. On Lossless Quantum Data Compression and Quantum Variable-Length Codes. 6.1. Introduction. 6.2. Codes, Lengths, Kraft Inequality and yon Neumann Entropy Bound. 6.2.1. The Codes. 6.2.2. Length Observable and Average Length of Codewords. 6.2.3. Kraft Inequality and yon Neumann Entropy Bound. 6.2.4. Base Length. 6.3. Construct Long Codes from Variable-Length Codes. 6.4. Lossless Quantum Data Compression, if the Decoder is Informed about the Base Lengths. 6.5. Code Analysis Based on the Base Length. 6.6. Lossless Quantum Data Compression with a Classical Helper. 6.7. Lossless Quantum Data Compression for Mixed State Sources. 6.8. A Result on Tradeoff between Quantum and Classical Resources in Lossy Quantum Data Compression. References. Chapter 7. Entanglement Properties of Composite Quantum Systems. 7.1. Introduction. 7.2. Separability of Composite Quantum Systems. 7.2.1. The Separability Problem. 7.2.2. Results on The Separability Problem. 7.3. The Distillability Problem. 7.3.1. Results on the Distillability Problem. 7.4. Witness Operators for the Detection of Entanglement. 7.4.1. Definition and Geometrical Interpretation of Witness Operators. 7.4.2. Results on Witness Operators. 7.5. Quantum Correlations in Systems of Fermionic and Bosonic States. 7.5.1. What is Different with Indistinguishable Particles? 7.5.2. Results on Quantum Correlations for Indistinguishable Particles. 7.5.3. hnplementation of an Entangling Gate with Bosons. 7.6. Summary. References. Chapter 8, Non-Classical Gaussian States in Noise Environments. 8.1. Introduction. 8.2. Classicality. 8.2.1. Classicality. 8.2.2. CP Maps and Partial Measurements. 8.2.3. Separability and Entanglement. 8.3. Entangle- ment Degradation. 8.4. Quantum Teleportation in Noise Environments. 8.4.1. Imperfect Teleportation. 8.4.2. Teleportation Fidelity, 8.4.3. Choice of the Coherent Displacement. References. Chapter 9. Quantum Estimation with Finite Resources. 9.1. Introduction. 9.2. Quantum Devices and Channels. 9.3. Estimating Quantum channels. 9.4. Entanglement and Estimation. 9.4.1. Estimation Using Single Qubits. 9.4.2. Estimation Using Entangled States. 9.5. Generalized Estimation with Two Channels. 9.5.1. Estimation with Two Channels. 9.5.2. What is the Optimal Reference Channel? 9.5.3. Estimation with Werner States. 9.6. Outlook. References. Chapter 10. Size Scaling of Decoherence Rates. 10.1. Introduction. 10.2. Decoherence Models. 10.3. Collective and Independent Decoherence. 10.4. Average Decoherence Rate as a Measure of Decoherence. 10.5. Decoherence Rate Scaling due to Partially Correlated Fields. 10.6. Conclusion. References. Chapter 11. Reduced Collective Description of Spin-Ensembles. 11.1. Introduction. 11.2. Operation Representa- tions. 11.3. Hamilton Models. 11.3.1. Symmetry-Constrained Networks. 11.3.2. Topology-Constained Networks. 11.4. State Model. 11.4.1. Totally Permutation-Symmetric Subspa~e. 11.4.2. Collective 1-Particle Excitations. 11.4.3. 1-Parameter Families of Non-Pure States. 11.4.4. Families of Separable States: "Modules". 11.5. Ensem- bles. 11.5.1. Trajectories and Ergodicity. 11.5.2. Leakage and Storage Capacity. 11.5.3. Mixing Stratgies. 11.5.4. State Construction and Separability. 11.6. Summary and Outlook. References. Chapter 12. Quantum Information Processing with Defects. 12.1. Introduction. 12.2. Properties of Nitrogen- Vacancy Centers in Diamond. 12.3. Readout of Spin State via Site-Selective Excitation. 12.4. Magnetic Resonance on a Single Spin at Room Temperature. 12.5. Magnetic Resonance on a Single 13C Nuclear Spin. 12.6. Two-Qubit Gate with Electron Spin and 13C Nuclear Spin of Single NV Defect, 12.7. Outlook: Towards Scalable NV Based Quantum Processor. References. Chapter 13. Quantum Dynamics of Vortices and Vortex Qubits. 13.1. Introduction. 13.2. Macroscopic Quantum Effects with Single Vortices. 13.2.1. Quantum Tunneling. 13.2.2. Energy Level Quantization. 13.3. Vortex- Antivortex Pairs. 13.3.1. Thermal and Quantum Dissociation. 13.3.2. Energy Levels of a Bound Vortex- Antivortex Pair. 13.4. The Josephson Vorex Qubit. 13.4.1. Principle of the Vortex Qubit. 13.4.2. Model. 13.4.3. Perturbative Calculation of Vortex Potential. 13.4.4. Quantum Mechanics of a Vortex in a Double Well. 13.4.5. Depinning Current and Qubit Readout. 13.5. Conclusions. References. Chapter 14. Decoherence in Resonately Driven Bistable Systems. 14.1. Introduction. 14.2. The model and its Symmetries. 14.3. Coherent Tunneling. 14.4. Dissipative Tunneling. 14.5. Conclusions. References.

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Chapter 15. Entanglement and Decoherence in Cavity QED with a Trapped Ion. 15.1. Introduction. 15.2. Deco- herence Effects. 15.3. Greenberger-Horne-Zeilinger State. 15.4. Photon-Number Control. 15.5. Entanglement of Separated Atoms. 15.6. Summary. References. Chapter 16. Quantum Information Processing with Ions Determinlstically Coupled to an Optical Cavity. 16.1. Introduction. 16.2. Deterministic Coupling of Ions and Cavity Field. 16.3. Single-Ion Mapping of Cavity-Modes. 16.4. Atom-Photon Interface. 16.5. Single-Photon Source. 16.6. Cavity-Mediated Two-Ion Coupling. References. Chapter 17. Strongly-Coupled Atom-Cavity Systems. 17.1. Introduction. 17.2. Atoms, Cavities and Light. 17.2.1. Field Quantization in a Fabry-Perot Cavity. 17.2.2. Two-Level Atom. 17.2.3. Three-Level Atom. 17.2.4. Adiabatic Passage. 17.3. Single-Photon Sources. 17.3.1. Vacuum-Stimulated Raman Scattering. 17.3.2. Deterministic Single-Photon Sequences. 17.4. Summary and Outlook. References. Chapter 18. A Relation-Free Verification of the Quantum Zeno Paradox on an Individual Atom. 18.1. Introduc- tion. 18.2. The Hardware and Basic Procedure. 18.3. First Scheme: Statistics of the Sequences of Equal Results. 18.4. Second Scheme: Driving the Ion by Fractionated ~-Pulses. 18.5. Conclusions. 18.6. Survey of Related Work. References. Chapter 19. Spin Resonance with Trapped Ions: Experiments and New Concepts. 19.1. Introduction. 19.2. Self-Learning Estimation of Quantum States 19.3. Experimental Realization of Quantum Channels. 19.4. New Concepts for QIP with Trapped Ions. 19.4.1. Spin Resonance with Trapped Ions. 19.4.2. Simultaneous Cooling of Axial Vibrational Modes. 19.5. Raman Cooling of Two Trapped Ions. References. Chapter 20. Controlled Single Neutral Atoms as Qubits. 20.1. Introduction. 20.2. Cavity QED for QIP. 20.3. Single Atom Controlled Manipulation. 20.4. How to Prepare Exactly 2 Atoms in a Dipole Trap? 20.5. Optical Dipole Trap. 20.6. Relaxation and Decoherence. 20.7. Qubit Conveyor Belt. 20.8. Outlook. References. Chapter 21. Towards Quantum Logic with Cold Atoms in a CO2 Laser Optical Lattice. 21.1. Introduction. 21.2. Entanglement and Beyond. 21.3. Quantum Logic and Far-Detuned Optical Lattices. 21.4. Resolving and Addressing Cold Atoms in Single Lattice Sites. 21.5. Recent Work. References. Chapter 22. Quantum INformaiton Processing with Atoms in Optical Micro- Structures. 22.1. Introduction. 22.2. Microoptical Elements for Quantmn Information Processing. 22.3. Experimental Setup. 22.4. Scalable Qubit Registers Based on Arrays of Dipole Traps. 22.5. Initialization, Manipulation, and Readout. 22.6. Variation of Trap Separation. 22.7. Implementation of Qubit Gates. References. Chapter 23. Quantum Information Processing with Neutral Atoms on Atom Chips. 23.1. Introduction. 23.2. The Atom Chip. 23.2.1. Combined Magneto-Electric Traps. 23.2.2. RF-Induced Adiabatic Potentials for Manipulating Atoms. 23.2.3. Imperfections in the Atom Chip: Disorder Potentials. 23.3. The Qubit. 23.4. Entangling Qubits. 23.4.1. Quantum Gate via Cold Controlled Collisions. 23.4.2. Motional Qubit Gates with Controlled Collisions. 23.5. Input/Output. 23.5.1. Qubit Detection. 23.5.2. Quantum Input/Output. 23.6. Noise and Decoherence. 23.7. Summary and Conclusion. References. Chapter 24. Quantum Gates and Algorithms Operating on Molecular Vibrations. 24.1. Introduction. 24.2. Qubit States Encoded in Molecular Vibrations. 24.3. Optimal Control Theory for Molecular Dynamics. 24.3.1. Local Quantum Gates. 24.4. Multi-Target OCT for Global Quantum Gates. 24.4.1. Global Quantum Gates for Molecular Vibrational Qubits. 24.5. Basis Set Independence and Quantum Algorithms. 24.6. Towards More Complex Molecular Systems. 24.7. Outlook. References. Chapter 25. Fabrication and Measurement of Aluminum and Niobium Based Single-Electron TRansistors and Charge Qubits. 25.1. Introduction. 25.2. Motivation for this Work. 25.3. Sample Preparation. 25.3.1. SCheme of the Junction Preparation Technique. 25.3.2. Fabrication of Tunnel Devices: SET and Charge Qubit Structures. 25.4. Experimental Results. 25.5. Conclusions. References. Chapter 26. Quantum Dot Circuits for Quantum Computation. 26.1. Introduction. 26.2. Realizing Quanatum Bits in Double Quantum Dots. 26.3. Controlling the Electron Spin in Single Dots. 26.4. Summary. References. Chapter 27. Manipulation and Control of Individual Photons and Distant Atoms via Linear Optical Elements. 27.1. Introduction. 27.2. Manipulation and Control of Individual Photons via Linear Optical Elements. 27.2.1. Teleportation hnplementation of Non-Deterministic NLS Gate and Single-Mode Photon Filter. 27.2.2. Imple- mentation of Non-Deterministic NLS Gate via Parametric Amplifiers. 27.2.3. Phase Measurement of Light and Generation of Superposition of Fock States. 27.2.4. Joint Measurement of Photon Number Sum and Phase Dif- ference Operators on a Two-Mode Field. 27.2.5. Remark. 27.3. Quantum Entanglement Between Distant Atoms Trapped in Different Optical Cavities. 27.3.i. Generation of W States, GHZ States, and Cluster States Based on Single-Photon Detectors. 27.3.2. Generation of W States and GHZ States Based on Four-Photon Coincidence Detection. 27.4. Conclusion. References. Chapter 28. Conditional Linear Optical Networks. 28.1. Introduction. 28.2. Measurement-Induced Nonlinearities. 28.2.1. Beam Splitters and Networks. 28.2.2. Post-Processing of Single-Photon Sources and Number-Resolving Detectors. 28.3. Probability of Success and Permanents. 28.4. Upper Bounds on Success Probabilities. 28.5. Extension Using Weak Nonlinearities. References, Chapter 29. Multiphoton Entanglement. 29.1. Introduction. 29.2. Entangled Multiphoton State Preparation. 29.3. Experiment. 29.4. Quantum Correlations. 29.5. Bell Inequality. 29.6. Genuine Four-Photon Entanglement. 29.7. Entanglement Persistence. 29.8. Conclusions. References. Chapter 30. Quantum Polarization for Continuous Variable Information Processing. 30.1. Introduction. 30.2. Nonseparability and Squeezing. 30.2.1. Polarization Squeezing. 30.2.2. Continuous Variable Polarization Entan- glement. 30.3. Applications. 30.4, Stokes Operators Questioned: DEgree of Polarization in Quantum Optics. References.

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Chapter 31. A Quantum Optical XOR Gate. 31.1. Introduction. 31.2. Double Bump Photons. 31.3. The XOR Gate. 31.4. Quad Bump Photons. 31.5. Outlook. References. Chapter 32. Quantum Fiber Solitons--Generation, Entanglement, and Detection. 32.1. Introduction. 32.2. Quantum Correlations and Entanglement. 32.3. Multimode Quantum Correlations. 32.4. Generation of Bright Entangled Beams. 32.5. Detection of Entanglement of Bright Beams. 32.5.1. Sub-Shot-Noise Phase Quadrature Measurements on Intense Beams. 32.5.2. Direct Experimental Test of Non-Separability. 32.6. Entanglement Swapping. 32.7. Polarization Variables. References. Index.

Chemical Micro Process Enqineerinq: Processinq and Plants. Volker Hessel, Holger LSwe, Andreas Miiller and Gunther Kolb. Wiley-VCH. Hoboken, NJ. 2005. 651 pages. $199.00. Contents: Preface. Abbreviations and Symbols. Chapter 1. Mixing of Miscible Fluids. 1.1. Mixing in Micro Spaces Drivers, Principles, Designs, and Uses. 1.1.1. 'Mixing Fields', a Demand Towards a More Knowledge-Based Approach--Room for Micro Mixers? 1.1.2. Drivers for Mixing in Micro Spaces. 1.1.3. Mixing Principles. 1.1.4. Means for Mixing of Micro Spaces. 1.1.5. Generic Microstructured Elements for Micro-Mixer Devices. 1.1.6. Experimental Characterization of Mixing in Microstructured Devices. 1.1.7. Application Fields and Types of Micro Channel Mixers. 1.2. Active Mixing 1.2.1. Electrohydrodynamic Translational Mixing. 1.2.1.1. Mixer 1 [M 1]: Electrohydrodynamic Micro Mixer (I). 1.2.1.2. Mixer 2 [M 2]: Electrohydrodynamic Micro Mixer (II). 1.2.1.3. Mixer 3 [M 31: Electrokinetic Instability Electroosmotic Flow Micro Mixer, First-Generation Device. 1.2.1.4. Mixer 4 [M 4]: Electrokinetic Instability Electroosmotic Flow Micro Mixer, Second-Generation Device. 1.2.1.5. Mixer 5 [M 5]: Electrokinetic Instability Micro Mixer by Zeta-Potential Variation. 1.2.1.6. Mixer 6 [M 6]: Electrokinetic Dielectrophoresis Micro Mixer. 1.2.1.7. Mixing Characterization Protocols/Simulation. 1.2.1.8. Typical Results. 1.2.2. Electro Rotational Mixing. 1.2.2.1. Mixer 7 [M 7]: Coupled Electrorotational Micro Mixer. 1.2.2.2. Mixing Characterization Protocols/Simulation. 1.2.2.3. Typical Results. 1.2.3. Chaotic Electroosmotic Stirring Mixing. 1.2.3.1. Mixer 8 [M 8]: Chaotic Electroosmotic Micro Mixer. 1.2.3.2. Mixing Characterization Protocols/Simulation. 1.2.3.3. Typical Results. 1.2.4. Magnetohydrodynamic Mixing.

1.2.4.1. Mixer 9 [M 9]: Magnetohydrodynamic Micro Mixer. 1.2.4.2. Mixing Characterization Protocols/Simu- lation. 1.2.4.3. Typical Results. 1.2.5. Air-Bubble Induced Acoustic Mixing. 1.2.5.1. Mixer 10 [M 10]: Acoustic Microstreaming Micro Mixer, Version 1. 1.2.5.2. Mixer 11 [M 11]: Acoustic Microstreaming Micro Mixer, Version 2. 1.2.5.3. Mixer 12 [M 12]: Design Case Studies for Micro Chambers of Acoustic Microstreaming Micro Mixer, Version 2. 1.2.5.3. Mixing Characterization Protocols/Simulation. 1.2.5.4. Typical Results. 1.2.6. Ultrasonic Mixing. 1.2.6.1. Mixer 13 [M 13]: Ultrasonic Micro Mixer. 1.2.6.2. Mixing Characterization Protocols/Simulation. 1.2.6.3. Typical Results. 1.2.7. Moving- and Oscillating-Droplet Mixing by Electrowetting. 1.2.7.1. Mixer 14 [M 141: Moving- and Oscillating-Droplet Micro Mixer. 1.2.7.2. Mixing Characterization Protocols/Simulation. 1.2.7.3. Typical Results. 1.2.8. Moving- and Oscillating-Droplet Mixing by Dielectrophoresis. 1.2.8.1. Mixer 15 [M 15]: Dielectrophoretic Droplet Micro Mixer. 1.2.8.2. Mixer 16 [M 16]: Electrical Phase-Array Panel Micro Mixer. 1.2.8.3. Mixer 17 [M 17]: Electrical Dot-Array Micro Mixer. 1.2.8.4. Mixing Characterization Proto- cols/Simulation. 1.2.8.5. Typical Results. 1.2.9. Bulge Mixing on STructured Surface Microchip. 1.2.9.1. Mixer 18 [M 18]: Structured Surface Microchip. 1.2.9.2. Mixing Characterization Protocols/Simulation. 1.2.9.3. Typi- cal Results. 1.2.10. Valveless Micropumping Mixing. 1.2.10.1. Mixer 19 [M 19]: Valveless Micropumping Micro Mixer. 1.2.10.2. Mixing Characterization Protocols/Simulation. 1.2.10.3. Typical Results. 1.2.11. Membrane- Actuated Micropumping Mixing. 1.2.11.1. Mixer 20 [M 20]: Membrane-Actuated Micropumping Micro Mixer. 1.2.11.2. Mixing Characterization Protocols/Simulation. 1.2.11.3. Typical Results. 1.2.12. Micro Impeller Mix- ing. 1.2.12.1. Mixer 21 [M 21]: Impeller Micro Mixer. 1.2.12.2. Mixer 22 [M 22]: Ferromagnetic Sphere-Chain Micro Mixer. 1.2.12.3. Mixing Characterization Protocols/Simulation. 1.2.12.4. Typical Results. 1.2.13. Mag- netic Micro-Bead Mixing. 1.2.13.1. Mixer 23 [M 23]: Magnetic Micro-Bead Micro Mixer. 1.2.14. Rotating-Blade Dynamic Micro Mixer. 1.3. Passive Mixing. 1.3.1. Vertical Y- and T-Type Configuration Diffusive Mixing. 1.3.1.1. Mixer 24 [M 24]: T-Type Micro Mixer. 1.3.1.2. Mixer 25 [M 25]: Y-Type Micro Mixer. 1.3.1.3. Mixer 26 [M 26]: Y-Type Micro Mixer with Venturi Throttle. 1.3.1.4. Mixer 27 [M 27]: Y-Type Micro Mixer with Extended Serpentine Path. 1.3.1.5. Mixer 28 [M 28]: T-Type Micro Mixer with Straight Path. 1.3.1.6. Mixing Characteri- zation Protocols/Simulation. 1.3.1.7. Typical Results. 1.3.2. Horizontally Bi-Laminating Y-Feed Mixing. 1.3.2.1. Mixer 29 [M 29]: Unfocused Horizontally Bi-Laminating Y- Feed Micro Mixer. 1.3.2.2. Mixing Characteriza- tion Protocols/Simulation. 1.3.2.3. Typical Results. 1.3.3. Capillary-Force, Self-Filling Bi-Lamiuating Mixing. 1.3.3.1. Mixer 30 [M 30]: Capillary-Force Self-Filling Bi- Laminating Micro Mixer. 1.3.3.2. Mixing Characteri- zation Protocol/Simulation. 1.3.3.3. Typical Results. 1.3.4. Cross-Injection Mixing with Square Static Mixing Elements. 1.3.4.1. Mixer 31 [M 31]: Cross-Shaped Micro Mixer with Static Mixing Elements. 1.3.4.2. Mixing Characterization Protocols/Simulation. 1.3.4.3. Typical Results. 1.3.5. Hydrodynamic Focusing Cross-Injection Mixing. 1.3.5.1. Mixer 32 [M32]: Hydrodynamic Focusing Cross-Injection Micro Mixer. 1.3.5.2. Mixing Char- acterization Protocols/Simulation. 1.3.5.3. Typical Results. 1.3.6. Geometric Focusing Bi-Laminating Mixing. 1.3.6.1. Mixer 33 [M 33]: Mixer 33 [M 33]: Geometric Focusing Bi- Laminating Micro Mixer. 1.3.6.2. Mixing Characterization Protocols/Simulation. 1.3.6.3. Typical Results. 1.3.7. Bi-Laminating Microfluidic Networks for Generation of Gradients. 1.3.7.1. Mixer 34 [M 34]: Bi-Laminating Microfluidic Network. 1.3.7.2. Experimental

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Characterization Protocols/Siinulation. 1.3.7.3. Typical Results. 1.3.8. Bifurcation Multi-Laminating Difusive Mixing. 1.3.8.1. Mixer 35 [M 35]: Bifurcation Multi-Laminating Micro Mixer. 1.3.8.2. Mixing Characterization Protocols/Simulation. 1.3.8.3. Typical Results. 1.3.9. Interdigital Multi-Laminating Diffusive Mixing (Normal and Focusing). 1.3.9.1. Mixer 36 [M 36]: Unfocused Interdigital Multi-Laminating Micro Mixer with Co-Flow Injection Scheme (I), 'Rectangular Mixer'. 1.3.9.2. Mixer 37 [M 37]: Interdigital Vertically Multi- Laminating Mi- cro Mixer with Co-Flow Injection Scheme (II). 1.3.9.3. Mixer 38 [M 38]: Interdigital Horizontally Bi-Laminating Micro Mixer with Cross-Flow Injection Scheme, Reference Case to [M 37]. 1.3.9.4. Mixer 39 [M 39]: Interdigital Horizontally Multi- Laminating Micro Mixer with Co-Flow Injection Scheme. 1.3.9.5. Mixer 40 [M 40]: Inter- digital Vertically Multi- Laminating Micro Mixer with Counter-Flow Injection Scheme--'3-D Slit Mixer'. 1.3.9.6. Mixer 41 [M 41]: Interdigital Vertically Multi- Laminating Micro Mixer with Counter-Flow Injection Scheme, 10-Fold Array. 1.3.9.7. Mixer 42 [M 42]: Interdigital Vertically Multi- Laminating Micro Mixer with 'Slit-Type' Focusing--'Plane Slit Mixer'. 1.3.9.8. Mixer 43 [M 43]: Interdigital Vertically Multi- Laminating Micro Mixer with Triangular Focusing (I). 1.3.9.9. Mixer 44 [M 44]: Interdigital Vertically Multi- Laminating Micro Mixer with Optimized Triangular Focusing--'Superfocus'. 1.3.9.10. Mixer 45 [M 45]: Interdigital Vertically Multi- Laminating Micro Mixer with Triangular Focusing Zone (II). 1.3.9.11. Mixer 46 [M 46]: Interdigital Vertically Multi- Laminating Micro Mixer with Flow-Re-Directed Focusing Zone. 1.3.9.12. Mixing Characterization Proto- cols/Simulation. 1.3.9.13. Typical Results. 1.3.10. Interdigital Concentric Consecutive Mixing. 1.3.10.1. Mixer 47 [M 47]: Interdigital Consecutive Micro Mixer, StarLam300. 1.3.10.2. Mixer 48 [M 48]: Interdigital Consecutive Micro Mixer, StarLam3000. 1.3.10.2. Mixing Characterization Protocols/Simulation. 1.3.10.3. Typical Results. 1.3.11. Cyclone Laminating Mixing. 1.3.11.1. Mixer 49 [M 49]: Cyclone Laminating Micro Mixer, Tangential Injection (I). 1.3.11.2. Mixer 50 [M 50]: Cyclone Laminating Micro Mixer, Tangential Injection (II). 1.3.11.3. Mixer 51 [M 51]: Cyclone Laminating Micro Mixer, Cross- Flow Injection. 1.3.11.4. Mixing Characterization Protocols/Simulation. 1.3.11.5. Typical Results. 1.3.12. Concentric Capillary-in-Capillary and Capillary-in-Tube Mixing. 1.3.12.1. Mixer 52 [M 52]: Capillary-in-Capillary Micro Mixer. 1.3.12.2. Mixer 53 [M 53]: Capillary-in- Tube Micro Mixer. 1.3.12.3. Mixing Characterization Protocols/Simulation. 1.3.12.4. Typical Results. 1.3.13. Droplet Separation-Layer Mixing. 1.3.13.1. Mixer 54 [M 54]: Concentric Separation-Layer Interdigital Micro Mixer. 1.3.13.2. Mixer 55 [M 55]: Planar Separation-Layer Interdigital Micro Mixer. 1.3.13.3. Mixing Charac- terization Protocols/Simulation. 1.3.13.4. Typical Results. 1.3.14. Split-and-Recombine Mixing. 1.3.14.1. Mixer 56 [M 56]: MSbius-Type Split-and-Recombine Micro Mixer. 1.3.14.2. Mixer 57 [M 57]: MSbius-Type Split-and- Recombine Micro Mixer with Fins. 1.3.14.3. Mixer 58 [M 58]: Fork-Element Split-and-Recombine Micro Mixer. 1.3.14.4. Mixer 59 [M 59]: Stack Split-and-Recombine Micro Mixer. 1.3.14.5. Mixer 60 [M 60]: Up-Down Curved Split-and-Recombine Micro Mixer. 1.3.14.6. Mixer 61 [M 61]: Multiple-Collisions Split-and- Recombine Micro Mixer. 1.3.14.7. Mixer 62 [M 62]: Separation-Plate Split-and-Recombine Micro Mixer. 1.3.14.8. Mixing Char- acterization Protocols/Simulation. 1.3.14.9. Typical Results. 1.3.15. Rotation-and-Break-Up Mixing. 1.3.15.1. Mixer 63 [M 63]: Rotation-and-Break-Up Micro Mixer (I). 1.3.15.2. Mixer 64 [M 64]: Rotation-and-BReak-Up Micro Mixer (II). 1.3.15.3. Mixing Characterization Protocols/Simulation. 1.3.15.4. Typical Results. 1.3.16. Micro-Plume Injection Mixing. 1.3.16.1. Mixer 65 [M 65]: Micro-Plume Injection Micro Mixer. 1.3.16.2. Mixing Characterization Protocols/Simulation. 1.3.16.3. Typical Results. 1.3.17. Slug Injection Mixing. 1.3.17.1. Mixer 66 [M 66]: Segmented-Flow Micro Mixer. 1.3.17.2. Mixing Characterization Protocols/Simulation. 1.3.17.3. Typ- ical Results. 1.3.18. Secondary Flow Mixing in Zig-Zag Micro Channels. 1.3.18.1. Mixer 67 [M 67]: Y-Type Micro Mixer with Zig-Zag or Straight Channel. 1.3.18.2. Mixer 68 [M 68]: T-Type Micro Mixer with Zig-Zag or Straight Channel. 1.3.18.3. Mixing Characterization Protocols/Simulation. 1.3.18.4. Typical Results. 1.3.19. Mixing by Helical Flows in Curved and Meander Micro Channels. 1.3.19.1. Mixer 69 [M 69]: Curved Chan- nel Micro Mixer. 1.3.19.2. Mixer 70 [M 70]: Meander Channel Micro Mixer. 1.3.19.3. Mixer 71 [M 71]: 3-D L-Shaped Serpentine Micro Mixer. 1.3.19.4. Mixing Characterization Protocols/Simulation. 1.3.19.5. Typical Results. 1.3.20. Distributive Mixing with Traditional Static Mixer Designs. 1.3.20.1. Mixer 72 [M 72]: Intersect- ing Elements Microstructured Mixer. 1.3.20.2. Mixer 73 [M 73]: Helical Elements Micro Mixer. 1.3.20.3. Mixing Characterization Protocols/Simulation. 1.3.20.4. Typical Results. 1.3.21. Passive Chaotic Mixing by Posing Grooves to Viscous Flows. 1.3.21.1. Mixer 74 [M 74]: Non-Grooved Channel--Reference Case. 1.3.21.2. Mixer 75 [M 75]: Oblique, Straight-Grooved Micro Mixer (I). 1.3.21.3. Mixer 76 [M 76]: Oblique, Asymmetrically Grooved Micro Mixer--Staggered Herringbone Mixer (SMH). 1.3.21.4. Mixer 77 [M 77]: Oblique, Straight-Grooved Micro Mixer (II). 1.3.21.5. Mixer 78 [M 78]: Diagonal-Grooved Micro Mixer. 1.3.21.6. Mixing Characterization Proto- cols/Simulation. 1.3.21.7. Typical Results. 1.3.22. Chaotic Mixing by Twisted Surfaces. 1.3.22.1. Mixer 79 [M 79]: Twisted Surface Micro Mixer. 1.3.22.2. Mixing Characterization Protocols/Simulation. 1.3.22.3. Typical Results. 1.3.23. Chaotic Mixing by Barrier and Groove Integration. 1.3.23.1. Mixer 80 [M 80]: Barrier-Embedded Micro Mixer with Slanted Grooves. 1.3.23.2. Mixer 81 [M 81]: Barrier-Embedded Micro Mixer with Helical Elements. 1.3.23.3. Mixing Characterization Protocols/Simulation. 1.3.23.4. Typical Results. 1.3.24. Distributive Mixing by Cross-Sectional Confining and Enlargement. 1.3.24.1. Mixer 82 [M 82]: Distributive Micro Mixer with Varying Flow Restriction. 1.3.24.2. Mixing Characterization Protocols/Simulation. 1.3.24.3. Typical Results. 1.3.25. Time-Pulsing Mixing. 1.3.25.1. Mixer 83 [M 83]: Time-Pulsing Cross-Flow Micro Mixer (I). 1.3.25.2. Mixer 84 [M 84]: Time-Pulsing Cross-Flow Micro Mixer (II). 1.3.25.3. Mixing Characterization Protocols/Simulation. 1.3.25.4. Typical Results. 1.3.26. Bimodal Intersecting Channel Mixing. 1.3.26.1. Mixer 85 [M 85]: Bimodal Intersecting Channel Micro Mixer. 1.3.26.2. Mixing Characterization Protocols/Simulation. 1.3.26.3. Typical Results. 1.3.27. Micro-Bead Interstices Mixing. 1.3.27.1. Mixer 86 [M 86]: Micro-Bead Interstices Micro Mixer. 1.3.27.2. Mixing Characterization Protocols/Simulation. 1.3.27.3. Typical Results. 1.3.28. Recycle-Flow Coanda Effect Mixing Based on Taylor Dispersion. 1.3.28.1 Mixer 87 [M 87]: Coanda-Effect Micro Mixer with Tesla

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Structures. 1.3.28.2. Mixing Characterization Protocols/Simulation. 1.3.28.3. Typical Results. 1.3.29. Recycle- Flow Mixing Based on Eddy Formation. 1.3.29.1. Mixer 88 [M 88]: Recycle-Flow Micro Mixer. 1.3.29.2. Mixing Characterization Protocols/Simulation. 1.3.29.3. Typical Results. 1.3.30. Cantilever-Valve Injection Micro Mixer. 1.3.30.1. Mixer 89 [M 89]: Cantilever-Valve Injection Micro Mixing. 1.3.30.2. Mixing Characterization Proto- cols/Simulation. 1.3.30.3. Typical Results. 1.3.31. Serial Diffusion Mixer for Concentration Gradients. 1.3.31.1. Mixer 90 [M 90]: Serial Diffusion Micro Mixer for Concentration Gradients. 1.3.31.2. Mixing Characterization Protocols/Simulation. 1.3.31.3. Typical Results. 1.3.32. Double T-Junction Turbulent Mixing. 1.3.32.1. Mixer 91 [M 91]: Double T-Junction Micro Mixer. 1.3.32.2. Mixing Characterization Protocols/Simulation. 1.3.32.3. Typical Results. 1.3.33. Jet Collision Turbulent or Swirling-Flow Mixing. 1.3.33.1. Mixer 92 [M 92]: Frontal- Collision Impinging Jet Micro Mixer, 'Micro Jet Reactor'. 1.3.33.2. Mixer 93 [M 93]: Y-Type Collision Impinging Jet Micro Mixer. 1.3.33.3. Mixer 94 [M 941: Impinging Jet Array Micro Mixer. 1.3.33.4. Mixing Characterization Protocols/Simulation. 1.3.33.5. Typical Results. References. Chapter 2. Micro Structured Fuel Processors for Energy Generation. 2.1. Outline and Definitions. 2.1.1. Power Range and Applications. 2.1.2. Overall Assembly. 2.1.3. Definitions. 2.2. Factors Affecting the Competitiveness of Fuel Processors. 2.2.1. Costs. 2.2.2. Efficiency. 2.2.3. Start-Up Time. 2.2.4. Size. 2.2.5. Weight. 2.2.6. Responsiveness to Load Changes. 2.2.7. Lifetime. 2.3. Design Concepts of Micro Structured Reactors for Fuel Processing Applications. 2.4. Micro Structured Test Reactors for Fuel Processing. 2.4.1. Methanol Stream Re- forming (MSR) 2.4.1.1. Methanol Steam Reforming 1 [MSR 1]: Electrically Heated Serpentine Channel Chip-Like Reactor. 2.4.1.2. Methanol Steam Reforming 2 [MSR 2]: Electrically Heated Parallel Channel Chip-Like Reac- tor. 2.4.1.3. Methanol Steam Reforming 3 [MSR 3]: Electrically Heated Stack-Like Reactor. 2.4.1.4. Methanol Steam Reforming 4 [MSR 4]: Externally Heated Stack-Like Reactor. 2.4.1.5. Methanol Steam Reforming 5 [MSR 5]: Electrically Heated Stack-Like Reactor. 2.4.1.6. Methanol Steam Reforming 6 [MSR 6]: Electrically Heated Screening Reactor. 2.4.1.7. Development of Catalyst Coatings for Methanol Steam Reforming in Micro Channels. 2.4.2. Autothermal Methanol Reforming. 2.4.2.1. Autothermal Methanol Reforming 1 [AMR 1]: Mi- cro Structured Autothermal Methanol Reformer. 2.4.2.2. Autothermal Methanol Reforming 2 [AMR 2]: Micro Structured String Reactor for Autothermal Methanol Reforming. 2.4.2.3. Catalyst Development for Methanol Decomposition. 2.4.3. Hydrocarbon Reforming. 2.4.3.1. Methane Steam Reforming. 2.4.3.2. Development of Catalyst Coatings for Methane Steam Reforming in Micro Channels. 2.4.3.3. Hydrocarbon Reforming 1 [HCR 1]: Micro Structured Monoliths for Partial Methane Oxidation. 2.4.3.4. Hydrocarbon Reforming 2 [HCR 2]: Partial Methane Oxidation Heat Exchanger/Reactor. 2.4.3.5. Hydrocarbon Reforming 3 [HCR 3]: Micro Structured AutothermM Methane Reformer. 2.4.3.6. Hydrocarbon Reforming 4 [HCR 4]: Compact Membrane Reactor for Autothermal Methan Reforming. 2.4.3.7. Hydrocarbon Reforming 5 [HCR 5]: Sandwich Reactors Applied to Propane Steam Reforming. 2.4.3.8. Hydrocarbon Reforming 6 [HCR 6]: Micro Structured Monoliths for Partial Propane Oxidation and Autothermal Reforming. 2.4.3.9. Catalyst Development for the Autothermal Reforming of Isooctane and Gasoline in Micro Structures. 2.5. Combustion in Micro Channels as Energy Source for Fuel Processors. 2.5.1. Catalytic Hydrogen Combustion. 2.5.1.1. Mechanistic Investigations of Hydrogen Combustion. 2.5.1.2. Catalytic Hydrogen Combustion 1 [CHC 1]: Single-Channel Micro Reactor for Catalytic Hydrogen Com- bustion. 2.5.1.3. Catalytic Hydrogen Combustion 2 [CHC 2]: Quartz-Glass Micro Reactor for Catalytic Hydrogen Combustion. 2.5.1.4. Catalytic Hydrogen Combustion 3 [CHC 3]: Combined Mixer/Cross-Flow Combustor/Heat Exchanger for Determination of the Kinetics of Hydrogen Oxidation. 2.5.1.5. Catalytic Hydrogen Combustion 4 [CHC 4]: Cross-Flow Combustor/Heat Exchanger for Hydrogen Oxidation. 2.5.1.6. Catalytic Hydrogen Com- bustion 5 [CHC 5]: Combination of a Mixer, a Cross-Flow Combustor/Heat Exchanger and a Heat Exchanger for Product Quenching for Hydrogen Oxidation. 2.5.2. Catalytic Combustion of Alcohol Fuels. 2.5.3. Catalytic Hydrocarbon Combustion (CHCC). 2.5.3.1. Catalytic Hydrocarbon Combustion 1 [CHCC 1]: Ceramic Micro Reactor for Butane Combustion. 2.5.3.2. Catalytic Hydrocarbon Combustion 2 [CHCC 2]: MEMS System for Butane Combustion. 2.5.3.3. Catalytic Hydrocarbon Combustion 3 [CHCC 3]: Silicon Micro Reactor for Butant Combustion. 2.5.4. Homogeneous Combustion in Micro Channels. 2.5.4.1. Modeling of Homogeneous Methane Combustion in Micro Channels. 2.5.4.2. Homogeneous Combustion in Micro Channels 1 [HCC 1]: Homogeneous Hydrogen Combustion in a Micro Combustor. 2.5.4.3. Homogeneous Combustion in Micro Channels 2 [HCC 2]: Homogeneous Hydrogen Combustion in a 2-D Micro Combustor. 2.6. Micro Structured Reactors for Gas Purifi- cation (CO Clean-Up). 2.6.1. Water-Gas Shift. 2.6.1.1. Simulation of the Effect of Integrating Heat-Exchange Capabilities into Water-Gas Shift Reactors. 2.6.1.2. Catalyst Testing for the Water-Gas Shift Reaction in Mi- cro STructures. 2.6.1.3. Water-Gas Shift i [WGS 1]: Stack-Like Reactor Applied to Water-Gas Shift Testing. 2.6.1.4. Water-Gas Shift 2 [WGS 2]: Stack-Like Reactor Applied to Water-Gas Shift. 2.6.1.5. Water-Gas Shift 3 [WGS 3]: Sandwich-Type Reactor ([HCR 4]) Applied to Water-Gas Shift Catalyst Testing. 2.6.2. Preferential Carbon Monoxide Oxidation. 2.6.2.1. Preferential Carbon Monoxide 1 [PrOx 1]: MEMS-Like Reactor Applied to Studies of the PrOx Reaction in Micro Channels. 2.6.2.2. Preferential Carbon Monoxide Oxidation 2 [PrOx 2]: Single-Plate Reactor Based on MEMS Technology. 2.6.2.3. Preferential Carbon Monoxide Oxidation 3 [PrOx 3]: Integrated Micro Structure Heat Exchanger for PrOx Applied in a 20kW Fuel Processor. 2.6.2.4. Preferen- tial Carbon Monoxide Oxidation 4 [PrOx 4]: Stack-Like Reactor Applied to PrOx. 2.6.2.5. Preferential Carbon Monoxide Oxidation 5 [PrOx 5]: Integrated Heat Exchanger/Reactor for PrOx. 2.6.2.6. Preferential Carbon Monoxide Oxidation 6 [PrOx 6]: Stack-Like Reactor Aplied to PrOx. 2.6.3. Micro Structured Membranes for CO Clean-Up. 2.6.3.1. Micro Structured Membranes for CO Clean-Up 1 [MMem 1]: Palladium-Based Reactor for Membrane-Supported Water-Gas Shift. 2.6.3.2. Micro Structured Membranes for CO Clean-Up 2 [MMem 2]: Palladium Membrane Micro Reactor. 2.6.3.3. Micro Structured Membranes for CO Clean-Up 3 [MMem 3]: Palla- dium Membranes in Micro Slits. 2.6.3.4. Micro Structured Membranes for CO Clean-Up 4 [MMem 4]: Supported

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Palladium Membrane. 2.6.3.5. Micro Structured Membranes for CO Clean-Up 5 [MMem 5]: Sputtered Tantalum Membrane. 2.6.3.6. Micro Structured Membranes for CO Clean-Up 6 [MMem 6]: Pd and Pd77Ag23 Membranes. 2.6.3.7. Micro Structured Membranes for CO Clean-Up 7 [MMem 7]: Free-Standing Pd, Pd/Cu, and Pd/Ag Membranes. 2.7. Integrated Micro Structured Reactor Fuel Processing Concepts. 2.7.1.1. Parametric Study for Coupling Highly Exothermic and Endothermic Reactions. 2.7.1.2. Co-Current OPeration of Combined Meso-Scale Heat Exchangers and Reactors for Methanol Steam Reforming. 2.7.1.3. Feasibility Study for Combined Methane Oxidation/Steam Reforming in an Integrated Heat Exchanger. 2.7.2, Integrated System Fuelled by Methanol. 2.7.2.1. Integrated Systems Fuelled by Methanol 1 [ISMol 1]: Integrated Methanol Fuel Processor (Casio). 2.7.2.2. Integrated Systems Fuelled by Methanol 2 [ISMol 2]: Integrated Methanol Fuel Processor (Motorola), 2.7.2.3. Integrated Systems Fuelled by Methanol 3 [ISMol 3]: Integrated Autothermal MEthanol Fuel Processor (Ballard). 2.7.2.4. Integrated Systems Fuelled by Methanol 4 [ISMol 4]: Integrated Methanol Steam Reforming Fuel Proces- sor for 20 kW Power Output. 2.7.2.5. Integrated Systems Fuelled by Methanol 5 [ISMol 5]: Integrated Methanol Fuel Processor for 100 W Power Output. 2.7.2.6. Integrated Systems Fuelled by Methanol 6 [ISMol 6]: Integrated Methanol Fuel Processor for 15W Power Output. 2.7.2.7. Integrated Systems Fuelled by Methanol 7 [ISMol 7]: Integrated Methanol Fuel Processor for the Sub-Watt Power Range. 2.7.2.8. Integrated Systems Fuelled by Methanol 8 [ISMol 8]: Integrated Reformer/Combustor Reactor. 2.7.2.9. Integrated Systems Fuelled by Methanol 9 [ISMol 9]: Chip-Like Methanol Reformer/Combustor. 2.7.2.10. Integrated Systems Fuelled by Methanol 10 [IS- Mol 10]: Micro Integrated Heat Exchanger/Reactor for Methanol Steam Reforming. 2.7.2.11. Integrated Systems Fuelled by Methanol 11 [ISMol 11]: Micro Integrated Heat Exchanger/Fixed-Bed Reactor for Methanol Steam Reforming. 2.7.2.12. Integrated Systems Fuelled by Methanol 12 [ISMol 12]: Integrated Mechanol Evaporator and Hydrogen Combustor. 2.7.2.13. Integrated Systems Fuelled by Methanol 13 [ISMol 13]: Integrated Methanol Evaporator and Methanol Reformer. 2.7.3. Integrated System Fuelled by Methane. 2.7.3.1. Integrated Systems Fuelled by Methane 1 [ISM 1]: Integrated Reformer/Combustor Reactor. 2.7.3.2. Integrated Systems Fuelled by Methane 2 [ISM 2]: Integrated Reformer/Combustor Reactor. 2.7.3.3. Design Study for the Multi-Stage Adiabatic Mode. 2.7.4. Integrated Systems Running on Various Fuels. 2.7.4.1. Integrated Systems Running on Various Fuels 1 [ISV 1]: Integrated Evaporator/Burner Device for Automotive Applications. 2,7.4.2. Integrated Systems Running on Various Fuels 2 [ISV 2]: Combined System of Integrated Reformer/Heat Exchanger and Evapora- tor/Heat Exchanger Devices for Automotive Applications. 2.7.4.3. Integrated Systems Running on Various Fuels 3 [ISV 3]: Combined System of Integrated Reformer/Heat Exchanger and Evaporator/Heat Exchanger Devices for Automotive Applications. 2.7.4.4. Integrated Systems Running on Various Fuels 4 [ISV 4]: Integrated Evap- orator/Reformer/Burner Device for Automotive Applications. 2.7.4.5. Integrated Systems Running on Various Fuels 5 [ISV 5]: Combined Evaporator/Reformer/Burner Device. 2.7.4.6. Integrated Systems Running on Various Fuels 6 [ISV 6]: Integrated Reformer/Burner Device for Various Fuels. 2.7.4.7. Integrated Systems Running on Various Fuels 7 [ISV 7]: Integrated Steam Reformer/Heat Exchanger for Isooctane. 2,7.4.8. Integrated Systems Running on Various Fuels 8 [ISV 8]: Design of an Integrated MEMS Reformer/Burner Device for Butane. 2.8. Comparison of Micro Structured Fuel Processor Systems with Conventional Technologies. 2.8.1.1. Comparison on a Larger Scale Between a Shell and a Tube Heat Echanger, a Porous Metal Structure and a Plate and Fin Heat Exchanger Applied to Preferential CO Oxidation. 2.8.1.2. Comparison Between Packed Bed and Coating in Micro Tubes Applied to Methanol Steam Reforming. 2.8.1.3. Comparison Between Coated Micro Structures and a Conventional Monolith Applied to Autothermal Methanol Reforming. 2.8.1.4. Comparison Between a Micro Structured Monolith and Convential Monoliths Applied to Partial Oxidation of Methane. 2.8.1.5. Comparison Between Coated Micro Structures and a Conventional Monolith Applied to Water-Gas Shift. 2.8.1.6. Compari- son Between Coated Micro Structures and a Conventional Monolith Applied to Preferential Oxidation of Carbon Monoxide. 2.9. Fabrication Techniques for Micro Structured Energy Generation Systems. 2.9.1. Materials Ap- plied. 2.9.2. Micro Structuring Techniques. 2.9.2.1. Micro Milling. 2.9.2.2. Electrodischarge Machining. 2.9.2.3. Wet Chemical Etching. 2.9.3.4. Punching. 2.9.3.5, Embossing. 2.9.3.6. Laser Micro Machining (Ablation). 2.9.3.7. Sintering. 2.9.3. Bonding Techniques. 2.9.3.1. Gaskets. 2.9.3.2. Conventional Welding. 2.9.3.3. Laser Welding. 2.9.3.4. Electron Beam Welding. 2.9.3.5. Diffusion Bonding. 2.9.3.6. Brazing. 2.9.3.7. Sintering. 2.10. Catalyst Coating Techniques for Micro Structures and Their Application in Fuel Processing. 2.10.1. Coating of Ready-Made Catalyst. 2.10.2. Wash Coating. 2.10.3. Spray Coating. 2.10.4. Sol-Gel Coating. 2.10.5. Anodic Oxidation. 2.10.6. Electrophoretic Deposition. 2.10.7. Oxidation of FeCrAlloys. 2.10.8. Introduction of ZSM-5 Zeolite into Micro Channels. References. Chapter 3. Catalyst Screening. 3.1. Introduction. 3.1.1. Catalyst Screening During the Last Decade. 3.1.2. Current Situation and Future Challenges for Catalyst Screening. 3.1.2.1. Library Size and Design. 3.1.2.2. Sample Handling and Characterization. 3.1.2.3. Auatomated Measurement and Analysis. 3.1.2.4. Data Handling. 3.1.2.5. In Situ Surface Science Studies to Provide Micro Kinetics. 3.1.2.6. Multidisciplinary Knowledge Beyond Chemistry and Chemical Engineering Needed for Future Catalyst Screening. 3.1.3. Features of Chemical Micro Process Engineering to Impact on Catalyst Screening. 3.1.3.1. Flow Conditions in Small-Sized Reactors. 3.1.3.2. Analytical Expressions of Laminar FLow for Consolidation of SCreening Experiments. 3.1.3.3. Impact of Laminar- Flow Descriptions on Computational Evaluation Methods. 3.1.3.4. Heat "transport and Thermal Overshooting. 3.1.3.5. Exploration of Novel Reaction Regimes by Micro-Space Operation. 3.1.3.6. Up-Scaling. 3.1.4. Structure of the Contents of the Chapter. 3.2. Catalyst Preparation Methodology. 3.2.1. Catalyst Deposition. 3.2.1.1. Manual Impregnantion Procedure. 3.2.1.2. Semi-Auatomated Impregnation Method. 3.2.1.3. Catalyst Powder Injection. 3.2.1.4. Catalyst Pellet Preparation. 3.2.1.5. Parallel Sputter Coating. 3.3. Parallel Batch Screening Reactors. 3.3.1. Reactor 1 [R 1]: Agitated Mini-Autoclaves. 3.3.2. Reactor 2 [R 2]: Agitated Mini-Autoclaves. 3.3.3. Reactor 3 [R 3]: Agitated Mini-Autoclaves. 3.3.4. Lawn-Format Assays, 3.3.5. Catalyst Screening by

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Multistep Synthesis. 3.4. Screening Reactors for Steady Continuous Operation. 3.4.1. Multiple Micro Channel Array Reactors. 3.4.1.1. Reactor 4 [R 4]: Stacked Platelet Screening System. 3.4.1.2. Reactor 5 [R 5]: 10- Fold Parallel Reactor with Echangeable Flow Distribution Section. 3.4.1.3. Reactor 6 [R 6]: Micro Reactor for Steam Reforming Catalyst Testing. 3.4.1.4. Reactor 7 [R 7]: High-Throughput Micro Reactor with Parallel Micro Compartments. 3.4.1.5. Reactor 8 [R 8]: Modular SCreening Reactor Unit. 3.4.2. Chip-Type Reactors. 3.4.2.1. Reactor 9 [R 9]: Labratory Automaton Integrated Chip- Like Microsystem. 3.4.2.2. Reactor 10 [R 10]: Chip-Based Catalytic Reactor. 3.4.2.3. Reactor 11 [R 11]: Chemical Processing Microsystem. 3.4.3. Pellet- Type and Ceramic Reactors. 3.4.3.1. Reactor 12 [R 12]: Alumina Tablets Equipped Parallel Gas-Phase Reactor. 3.4.3.2. Reactor 13 [R 13]: Ceramic Monolith Reactor. 3.4.3.3. Reactor 14 [R 14]: High-Pressure Fixed-Bed Reactor. 3.4.3.4. Reactor 15 [R 15]: Multiple-Bead Pellet-Type Catalyst Carrier Reactor. 3.4.4. Well-Type Screening Reactors. 3.4.4.1. Infrared/Thermography Monitored Screening Reactor. 3.4.4.2. Reactor 16 [R 16]: Catalyst Filled Borings Reactor. 3.4.4.3. Reactor 17 [R 17]: Sputtered Catalyst Spots on Quartz Wafer Reactor. 3.4.4.4. Reactor 18 [R 18]: Polymerization Reactors Screening Reactor. 3.4.4.5. Reactor 19 [R 19]: Photochemical Active Catalyst Parallel Screening Reactor. 3.4.4.6. Reactor 20 [R 20]: Microstructured Chips with Catalyst- Coated Channels. 3.4.4.7. Reactor 21 [R 21]: 64-Channel Tubular Disk Fixed-Bed Reactor. 3.4.4.8. Reactor 22 [R 22]: The Microstructured Titer Plate Reactor Concept. 3.4.4.9. Physical Parameter Screening Reactor. 3.5. Reactors for Transient/Dynamic Operation. 3.5.1. Transient Operations in Microstructured Gas-Phase Reactors. 3.5.1.1. Reactor 23 [R 23]: Microstructured Titer Plate Transient Reactor Concept. 3.5.2. Dynamic Sequential Screening in Liquid/Liquid and Gas/Liquid Reactors. 3.5.2.1. Reactor 24 [R 24]: High-Throughput Gas/Liquid and Liquid/Liquid Dynamic Sequential Screening Reactor. 3.5.2.2. Multi-Port Valves, Injection Valves and Sensors. 3.6. Computational Evaluation Methods. 3.6.1. Evaluations Following Biological Means. 3.6.2. Numerical Evaluation Methods. 3.6.3. Kinetics Derived from Signal Dispersion. References. Chapter 4. Micro Structured Reactor Plant Concepts. 4.1. Micro Reactor or Micro Structured Reactor Plant (MRP). 4.2. Applicable Principles for Micro Structured Reactor Plant (MRP) Design. 4.2.1. Miniplant Techn- ology--A Model for the Micro Structured Reactor Plant Concept. 4.2.2. The Micro Unit Operations Concept. 4.2.3. Design Problems of Chemical Micro Structured Reactor Plants. 4.3. Process Conception and Economics 4.3.1. Market Study and Availability of Micro Structured Reactor Plant Design. 4.3.2. Pilot Study. 4.4. Early Concepts for Micro Structured Reactor Plant Design. 4.4.1. Paradigm Change Drives Miniplant Design Method- ology. 4.4.1.1. Reduction of Process Complexity for Distributed Chemical Manufacture. 4.4.1.2. Historical Analysis of Chemical Plant Development. 4.4.1.4. Supply-Chain Systems. 4.4.2. Reactor 1 [R 1]: Concept for an HCN Miniplant. 4.4.3. Reactor 2 [R 2]: Concept for a Disposable Construction Material. 4.4.3.1. Use of Polymers as a Disposable Construction Material. 4.4.3.2. Capacity of a Disposable Plant for HF Production. 4.5. Fluidic and Electrical Interconnects--Device-to-Device and Device-to- World. 4.5.1. Reactor 3 [R 3]: Fluidic Manifold Concept--Micro Structured Reactor-to-Micro Structured Reactor. 4.5.2. Reactor 4 [R 4]: Commer- cially Available Fluidic Interconnects- -Micro Structured Reactor-to-Micro Structured Reactor. 4.5.3. Reactor 5 [R 5]: Specially High-Pressure Fluidic Interconnect- -Chip-to-Chip. 4.5.4. Reactor 6 [R 6]: Specially Fluidic Sequencing Interconnect-- Chip-to-World. 4.5.5. Reactor 7 [R 7]: Electrical Interconnect for Fluid Driving-- Chip-to-World. 4.5.6. Reactor 8 [R 8]: Electrical Integrated Circuit Interconnect (ASIC)--Chip-to-World. 4.6. Table-Top Laboratory-Scale Plants. 4.6.1. Reactor 9 [R 9]: CPC Table-Top Reactors. 4.6.2. Reactor 10 [R 10]: Microinnova 'Chemical Production Anywhere' Concept. 4.6.3. Raector 11 [R 11]: Microinnova 'Lab Experiment Toolbox' Concept. 4.6.4. Reactor 12 [R 12]: Mikroglas Chemtech Micro Reaction System 'MikroSyn'. 4.6.5. Reactor 13 [R 13]: Modular Micro Reaction System FAMOS. 4.6.6. Reactor 14 [R 14]: EM Modular Microreac- tion System (Ehrfeld Mikrotechnik). 4.6.7. Reactor 15 [R 15]: Integrated Chemical Synthesizer. 4.6.8. Reactor 16 [R 16]: Integrated Micro Laboratory Disk Synthesizer. 4.6.9. Reactor 17 [R 17]: The NeSSI Modular Micro Plant Concept. 4.6.10. Reactor 18 [R 18]: The Micro Structured Reactor Backbone Interface Concept. 4.6.10.1. The Backbone Interface Concept. 4.6.10.2. Case Study 1 [C 1]: Physical Characterization of the Set-Up for an Enantioselective Synthesis. 4.6.10.3. Case Study 2 [C 2]: Chemical Characterization of the Backbone Using the Sulfonation of Toluene with Gaseous SOa. 4.7. Hybrid Plants. 4.7.1. Reactor 19 [R 19]: Micro Structured Reactor--Miniplant Hybrid Combination. 4.7.2. Reactor 20 [R 20]: Hybrid Methanol Steam Reformer. 4.7.3. Reactor 21 [R 21]: Hybrid Set-Up of Mini-Scaled and Micro Structured Components Inside a Reactor Housing. 4.8. Mobile Plants. 4.8.1. Reactor 22 [R 22]: Catalytic Automobile Exhaust Gas Converter. 4.8.1.1. Heating Performance. 4.8.1.2. Benchmarking to Exisiting Catalytic Converters. 4.9. Production Plants. 4.9.1. Reactor 23 [R 23]: Micro Structured Reactor Plant for Pigment Production. 4.9.2. Reactor 24 [R 24]: Micro Structured Reactor Plant for Hetrogeneously Catalyzed Gas-Phase Reactions. 4.9.3. Reactor 25 [R 25]: Micro Structured Reactor Plant for H202 Production. 4.10. Plant Installations and Supplier-Specific Assemblies. 4.11. Process Management. 4.11.1. Process Control and Automation. 4.11.1.1. Automation 1 [A 1] : Automated Micro Reaction System (AuM#Res). 4.11.1.2. Automation 2 [A 2]: MikroSyn Control System. 4.11.1.3. Automation 3 [A 3]: User-Adjustable Process Control System. 4.11.1.4. Automation 4 [A 4]: Sensor Analytical Manager. 4.11.2. Inline Analysis, Actuators and Sensorics. 4.11.2.1. Some Analytical Techniques Relevant for Micro-Channel Processing. 4.11.2.2. Automation 5 [A 5]: Inline Sensors According to the ISA SP76 Standard. 4.11.2.3. Automation 6 [A 6]: Micro Fabricated Neat-Infrared Fourier Transform Spectrometer. 4.11.2.4. Automation 7 [A 7]: Micro Fabricated Near-Infrared and Visible Spectrometer. 4.11.2.5. Automation 8 [A 8]: Micro Gas Chromatograph. 4.11.2.6. Automation 9 [A 9]: Electroanalytical Flow Cell. 4.11.2.7. Automation 10 [A 10]: High-Pressure Flow Cell for Optical Microscopic Observations. 4.11.2.8. Automation 11 [A 11]: Flow Cell for Optical Inspections. 4.11.2.9. Automation 12 [A 12]: Golden Cate® Single Reflection Diamond ATR Unit. 4.11.2.10. Automation 13 [A 13]: Combination of Inline Sensors with Electronic and Fluidic Bus Systems. 4.11.2.11. Automation 14 [A 14]: Booster

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Pumps. 4.11.3. Process Simulation. 4.11.3.1. Simulation 1 IS 1]: Micro Reaction Simuation Toolkit. 4.11.3.2. Simulation 2 [S 2]: Steady-State Process Simulator. 4.11.3.3. Simulation 3 [S 3]: Reactor Modeling for a Homo- geneous Catalytic Reaction. 4.12. Process Engineering. 4.12.1. Basic Engineering. 4.12.2. Detailed Engineering. 4.12.2.1. Engineering 1 [E 1]: Computer-Aided Plant Design Software. 4.12.2.2. Engineering 2 [E 2]: Process Analyzer and Sample- Handling System. 4.12.2.3. Engineering 3 [E 3]: The ttChemTech Piping Concept. 4.12.3. Scale-Up, Flow Distribution, and Interface to the Macroscopic World. 4.12.4. Calculation of Fluid Dynamics in Rectangular Channels. 4.12.4.1. Simulation of a Gas-Phase Reaction. 4.12.4.2. Residence Time Distribution for Guided Flow in Channels. 4.12.4.3. Residence Time Distribution for Non-Guided Flow. 4.12.4.4. Calculation of Cumulative Residence Time Distribution. 4.12.4.5. Calculations for Laminar- and Plug-Flow Reactors. 4.12.4.6. External Flow Distribution. 4.13. New Processes for Cost-Efficient Reactor Manufacturing. 4.13.1. Ceramic Foil Manufacturing. 4.13.2. Solder-Based Interconnection Techniques. 4.13.2.1. Channel Manufacturing by Copper Etching. 4.13.2.2. Typical Application--Micro CPU Cooler. 4.13.3. Printed Circuit Heat Exchanger Technology. 4.13.3.1. Stainless-Steel Diffusion Bonding. 4.13.3.2. Catalyst Carrier Coating Inside Bonded Reactors. 4.13.4. Online Reactor Manufacturing. 4.13.4.1. Continuous Coating Processes in the Polymer Industry. 4.13.4.2. Adap- tation of Industrial Online Processes to Micro Structured Reactor Manufacturing. 4.13.4.3. Production Modules. 4.13.4.4. Monolithic Heat Exchanger Manufacturing. References. Subject Index.

Flux-Corrected Transport. Principles, Algorithms, and Applications. Edited by D. Kuzmin, R. LShner and S. Turek. Springer. Heidelberg, Germany. 2005. 301 pages. $139.00. Contents: Foreword. Chapter 1. The Conception, Cestation, Birth, and Infancy of FCT. Chapter 2. The Design of Flux-Corrected Transport (FCT) Algorithms For Structured Grids. Chapter 3. On Monotonically Integrated Large Eddy Simulation of Turbulent Flows Based on FCT Algorithms. Chapter 4. Large Scale Urban Simulations with FCT. Chapter 5. 30 Years of FCT: Status and Directions. Chapter 6. Algebraic Flux Correction I. Scalar Conservation Laws. Chapter 7. Algebraic Flux Correction II. Compressible Euler Equations. Chapter 8. Algebraic Flux Correction III. Incompressible Flow Problems. Index.